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AlphaMonarch 7B AWQ by LoneStriker

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  4-bit   Autotrain compatible   Awq Base model:mlabonne/neuralmona... Base model:quantized:mlabonne/...   Conversational   Dpo   En   Endpoints compatible   Lazymergekit   Merge   Mistral   Quantized   Region:us   Rlhf   Safetensors
Model Card on HF 🤗: https://huggingface.co/LoneStriker/AlphaMonarch-7B-AWQ 

AlphaMonarch 7B AWQ Benchmarks

LLME Score: 0.13559
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
AlphaMonarch 7B AWQ (LoneStriker/AlphaMonarch-7B-AWQ)
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AlphaMonarch 7B AWQ Parameters and Internals

Model Type 
DPO, text-generation
Use Cases 
Areas:
research, commercial applications
Primary Use Cases:
Conversations, RP (Role Playing), Storytelling
Considerations:
Environments such as the Mistral Instruct chat template are recommended for optimal interaction style.
Additional Notes 
The model tends to exhibit a formal and sophisticated communication style.
Supported Languages 
en (High)
Training Details 
Data Sources:
mlabonne/truthy-dpo-v0.1, mlabonne/distilabel-intel-orca-dpo-pairs, mlabonne/chatml-OpenHermes2.5-dpo-binarized-alpha
Methodology:
DPO fine-tuning
Context Length:
8000
Hardware Used:
LazyMergekit
LLM NameAlphaMonarch 7B AWQ
Repository 🤗https://huggingface.co/LoneStriker/AlphaMonarch-7B-AWQ 
Base Model(s)  NeuralMonarch 7B   mlabonne/NeuralMonarch-7B
Model Size7b
Required VRAM4.2 GB
Updated2025-09-23
MaintainerLoneStriker
Model Typemistral
Model Files  4.2 GB
Supported Languagesen
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMistralForCausalLM
Licensecc-by-nc-4.0
Context Length32768
Model Max Length32768
Transformers Version4.37.2
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/AlphaMonarch-7B-AWQ.

Rank the AlphaMonarch 7B AWQ Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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